SOURCE-LINKED INTELLIGENCE

Deep Reinforcement Learning-Based Battery Management System for Electric Vehicles

CORDIS · observation · Publication date unknown

extending the battery lifetime. The interdisciplinary nature of DeepBMS is very strong, involving a combination of control and state estimation theory, power electronics, battery storage systems, and machine learning. The supervisor and candidate have excellent complemental research experiences in these fields providing the necessary competencies to bring the project to successful completion. The project ensures two-way transfer of knowledge including training of the candidate in cutting-edge advanced techniques in a state-of-the-art laboratory, which improves his future career prospects. Likewise, DeepBMS is in line with the EU strategic action plan on batteries and its results have a great potential to be further developed at the fundamental and applied levels through follow-up research. Batteries, State Estimation, Battery Management System

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recordType

award

status

SIGNED

region

EU

value

230774.4

unit

EUR